Future trends in 3D medical imaging

Coatrieux, Jean-Louis; Toumoulin, Christine; Hamon, C.; Luo, Ling

doi:10.1109/51.105216

Cited by 16 publications

(7 citation statements)

References 44 publications

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“…As diverse as the important contribution in segmentation and registration aspects, these applications have dominated most of the reported works [6], [21], [23], [30], [31]; and 3. The advancement for both algorithms development and optimisation as well as hardware implementation aspects lies as a result of intra-disciplinary advancement that involves medical specialities, industrial development, physics, engineering, computer science and mathematics [26], [28].…”

Section: Shams Et Al [6]mentioning

confidence: 99%

Efficient reconfigurable architectures for 3D medical image compression

Ahmad

Amira

2009

2009 International Conference on Field-Programmable Technology

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A AbstractRecently, the more widespread use of three-dimensional (3-D) imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US) have generated a massive amount of volumetric data. These have provided an impetus to the development of other applications, in particular telemedicine and teleradiology. In these fields, medical image compression is important since both efficient storage and transmission of data In summary, this research is tackling the issues of massive 3-D medical volumes data that requires compression as well as hardware implementation to accelerate the slowest operations in the system. Results obtained also reveal a significant achievement in terms of the architecture efficiency and applications performance.

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Section: Shams Et Al [6]mentioning

confidence: 99%

Efficient reconfigurable architectures for 3D medical image compression

Ahmad

Amira

2009

2009 International Conference on Field-Programmable Technology

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“…Conventionally, 3-D spatial information is either compressed into 2-D images in the form of projection planes from multiple angles or represented as different cross-sectional planes [1]. In medical applications, the inability to view the complete 3-D anatomy might result in misdiagnosis if the imaging angles and cross sections are not chosen properly [2].…”

Section: Introductionmentioning

confidence: 99%

Volumetric ultrasound imaging using 2-D CMUT arrays

Oralkan

Ergun

Cheng

et al. 2003

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

168

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Recently, capacitive micromachined ultrasonic transducers (CMUTs) have emerged as a candidate to overcome the difficulties in the realization of 2-D arrays for real-time 3-D imaging. In this paper, we present the first volumetric images obtained using a 2-D CMUT array. We have fabricated a 128 128-element 2-D CMUT array with through-wafer via interconnects and a 420-m element pitch. As an experimental prototype, a 32 64-element portion of the 128 128-element array was diced and flipchip bonded onto a glass fanout chip. This chip provides individual leads from a central 16 16-element portion of the array to surrounding bondpads. An 8 16-element portion of the array was used in the experiments along with a 128-channel data acquisition system. For imaging phantoms, we used a 2.37-mm diameter steel sphere located 10 mm from the array center and two 12-mm-thick Plexiglas plates located 20 mm and 60 mm from the array. A 4 4 group of elements in the middle of the 8 16-element array was used in transmit, and the remaining elements were used to receive the echo signals. The echo signal obtained from the spherical target presented a frequency spectrum centered at 4.37 MHz with a 100% fractional bandwidth, whereas the frequency spectrum for the echo signal from the parallel plate phantom was centered at 3.44 MHz with a 91% fractional bandwidth. The images were reconstructed by using RF beamforming and synthetic phased array approaches and visualized by surface rendering and multiplanar slicing techniques. The image of the spherical target has been used to approximate the point spread function of the system and is compared with theoretical expectations. This study experimentally demonstrates that 2-D CMUT arrays can be fabricated with high yield using silicon ICfabrication processes, individual electrical connections can be provided using through-wafer vias, and flip-chip bonding can be used to integrate these dense 2-D arrays with electronic circuits for practical 3-D imaging applications. Manuscript

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“…2 To tackle these problems, interactive workstation-based systems have been devised for visualizing and quantitating structures in 3D images.3'4'5 Unfortunately, these systems generally demand time-consuming, subjective, error-prone human interaction. To reduce the disadvantages of purely interactive techniques, some recent efforts have combined automatic image analysis with human interaction.610 These efforts demonstrate that for complex 3D medical applications, a judicious combination of human interaction and automatic computer-based processing is essential.…”

Section: Introductionmentioning

confidence: 99%

<title>Graphical user interface system for 3D medical image analysis</title>

et al. 1994

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The utility of three-dimensional (3D) medical images has been limited by difficulties in analyzing and making measurements on the images. To tackle these problems, interactive workstation-based systems have been devised for visualizing and quantitating structures in 3D images. Unfortunately, these systems generally demand timeconsuming, subjective, error-prone human interaction. To reduce the disadvantages of purely interactive techniques, some recent efforts have combined automatic image analysis with human interaction. These efforts demonstrate that for complex 3D medical applications, a judicious combination of human interaction and automatic computer-based processing is essential. We describe a system called INTERSEG (INTERactive SEGmentation) that combines human interaction and automatic processing for 3D radiological image analysis. INTERSEG is a graphical user interface system that can be used to: (1) construct interactively defined region cues; (2) invoke automatic image analysis; and (3) peruse/visualize analyzed images. The cues, which are easy to construct, convey problem-specific information and define the image-analysis task. The paper focuses on INTERSEG's capabilities for human interaction and visualization.

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Future trends in 3D medical imaging

Cited by 16 publications

References 44 publications

Efficient reconfigurable architectures for 3D medical image compression

Efficient reconfigurable architectures for 3D medical image compression

Volumetric ultrasound imaging using 2-D CMUT arrays

<title>Graphical user interface system for 3D medical image analysis</title>

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